血浆的综合蛋白质组学和代谢组学分析揭示了甲状腺癌的调节途径和关键因素。

IF 4.3 3区 材料科学 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC
Zijian Sun, Dongdong Feng, Liehao Jiang, Jingkui Tian, Jiafeng Wang and Wei Zhu
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引用次数: 1

摘要

甲状腺癌是最常见的内分泌恶性肿瘤,近年来发病率呈上升趋势。细针穿刺活检(Fine-needle穿刺活检,FNAB)作为甲状腺结节初步评估的金标准,未能涵盖所有的细胞病理条件,导致过度诊断。目前迫切需要对甲状腺癌和良性甲状腺结节(BTNs)进行更好的分类。本文对10例TC患者和15例btn患者的血浆样本进行了基于数据独立采集(DIA)的蛋白质组学和非靶向代谢组学研究。鉴定出TC特异性的关键蛋白和代谢物,并使用酶联免疫吸附试验(ELISA)进行独立队列验证潜在的生物标志物。共鉴定出1429种蛋白质和1172种代谢物。主成分分析显示,两组在蛋白质组水平上有很强的重叠,在代谢组水平上有明显的区别,表明甲状腺癌代谢组紊乱更为剧烈。蛋白质组学和代谢组学的综合分析表明甘油磷脂代谢和花生四烯酸代谢是关键的调控途径。此外,还建立了由LCAT、GPX3和白三烯B4组成的多组学生物标志物面板。根据发现集的AUC值,分类性能为0.960。外部验证集的AUC值为0.930。总之,我们的结果将有助于潜在的生物标志物在甲状腺癌诊断中的临床应用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Integrated proteomic and metabolomic analysis of plasma reveals regulatory pathways and key elements in thyroid cancer†

Integrated proteomic and metabolomic analysis of plasma reveals regulatory pathways and key elements in thyroid cancer†

Thyroid cancer (TC) is the most common endocrine malignancy with increasing incidence in recent years. Fine-needle aspiration biopsy (FNAB), as a gold standard for the initial evaluation of thyroid nodules, fails to cover all the cytopathologic conditions resulting in overdiagnosis. There is an urgent need for a better classification of thyroid cancer from benign thyroid nodules (BTNs). Here, data independent acquisition (DIA)-based proteomics and untargeted metabolomics in plasma samples of 10 patients with TC and 15 patients with BTNs were performed. Key proteins and metabolites were identified specific to TC, and an independent cohort was used to validate the potential biomarkers using enzyme-linked immunosorbent assay (ELISA). In total, 1429 proteins and 1172 metabolites were identified. Principal component analysis showed a strong overlap at the proteomic level and a significant discrimination at the metabolomic level between the two groups, indicating a more drastic disturbance in the metabolome of thyroid cancer. Integrated analysis of proteomics and metabolomics shows glycerophospholipid metabolism and arachidonic acid metabolism as key regulatory pathways. Furthermore, a multi-omics biomarker panel was developed consisting of LCAT, GPX3 and leukotriene B4. Based on the AUC value for the discovery set, the classification performance was 0.960. The AUC value of the external validation set was 0.930. Altogether, our results will contribute to the clinical application of potential biomarkers in the diagnosis of thyroid cancer.

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CiteScore
7.20
自引率
4.30%
发文量
567
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